Min. 1st Qu. Median Mean 3rd Qu. Max.
6583 13537718 33019610 43277808 57791802 267464092
Min. 1st Qu. Median Mean 3rd Qu. Max.
14833 74347 189134 321806 389481 3870379
This project will fit a model that uses GDP to predict CO2 emissions, exploring if there is a relationship between GDP and CO2 Emissions.
Alyssa Gurkas | December 9, 2024
Carbon dioxide (CO2) is a type of greenhouse gas, known for trapping heat, that is emitted into the atmosphere from burning fossil fuels (like coal, oil, and natural gas), and other natural processes like wildfires or volcanic eruptions.
CO2 in the atmosphere warms the planet, and causes global warming (or climate change). Human dependence on fossil fuels raised CO2 levels in the atmosphere. According to NASA, CO2 content in the atmosphere increased by 50% in less than 200 years. Source
The U.S. Department of Energy prepares an annual Electric Power Report that includes information about energy production, sales, consumption of fossil fuels, environmental data, and other topics related to energy. Additionally, the U.S. Department of Commerce tracks state annual summary statistics which include GDP by state from years 1998-2023.
This project uses data from the Department of Energy’s (DOE) Annual Electric Power Report and the U.S. Department of Commerce (DOC) State Annual Summary Statistics.
Each row represents the respective state’s annual energy usage and GDP for the reporting year. There are 1326 rows in the data set and eight columns.
To determine if there is a relationship between the CO2 emitted from energy production in the respective state, and the state GDP, a scatter plot can be used to visualize the linear relationship.
Texas and California seem to be outliers in this dataset. They have very large GDPs, and emit more CO2 than the other States. The data is also positively skewed. Due to this, a log transformation may be necessary to run a linear regression.
The non-linear Q-Q plot with the heavy tail indicates that there may be skewness in the residuals. This signals that the residuals are not normally distributed.
Producer Types (Business Classification): The EIA classifies Producer Types on page 227 of the Electric Power Annual 2023 Annual Report. On slide seven the Energy Producer Types were referenced.
Energy Source: The EIA defines renewable energy within the footnote section on page 33 of the Electric Power Annual 2023 Annual Report. On slide six Energy Sources were referenced.